Adsorption energy scaling relationships have now developed beyond their original form, which was more targeted towards the optimization of catalytic sites and the reduction of computational costs in simulations. The recent surge of interest in the adsorption energy scaling relations is to explore the surfaces beyond the transition metals (TMs) as well as reactions involving complicated molecules. Breakdown of such scaling relationships leads to motivating the discovery of novel catalysts with enhanced capabilities. In this work, we report our extensive study on the linear scaling relation (LSR) between oxygen (O), a group VIA element with elements of neighbouring groups such as: Group IIIA (Boron (B), Aluminum (Al)), IVA (Carbon (C), Silicon (Si)), VA (Nitrogen(N),phosphorus(P)) and VIIA (Florine(F)) on magnetic bimetallic surfaces. We found that the slope is positive for only O versus N and F, remaining of the slopes are negative. The present model is based on multiple surface descriptors, particularly spin-averaged d-band center and the surface's magnetic moment, whereas the original scaling theory (Phys. Rev. Lett. 99, 016105 (2007)) was based on a single adsorbate descriptor: adsorbate valency.
Lowering the Exponential Wall: Accelerating High-Entropy Alloy Catalysts Screening using Local Surface Energy Descriptors from Neural Network Potentials
Effect of Tube Radius on the Adsorption of Chlorothalonil on Single-Walled Carbon and Boron Nitride Nanotube Surfaces: A Theoretical Study for Environmental Remediation
Discovering Physically Interpretable Mathematical Expression for Predicting CO2 Adsorption in Metal-Organic Frameworks via Machine Learning-Symbolic Regression
The University of Edinburgh（爱丁堡大学）；Luleå University of Technology（吕勒奥理工大学）；Shanghai Jiao Tong University（上海交通大学）；Tsinghua University（清华大学）
Interpretable, Physics-Informed Learning Reveals Sulfur Adsorption and Poisoning Mechanisms in 13-Atom Icosahedra Nanoclusters
Federal University of Pelotas（佩洛塔斯联邦大学）；Universidade de Franca（弗兰卡大学）；Federal University of Paraná（巴拉那联邦大学）；Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；University of Brasília（巴西利亚大学）；Federal Institute of Amazonas（亚马孙联邦学院）
Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model Agent
Department of Chemical Engineering, Carnegie Mellon University（化学工程系，卡内基梅隆大学）；Department of Mechanical Engineering, Carnegie Mellon University（机械工程系，卡内基梅隆大学）
Covalent Adsorption of functional groups on [N]-carbophenes
Starting from the planar molecule 1,3,5-trihydroxybenzene, Du et al. reported synthesizing one of a couple of possible 2D materials: graphenylene or 3-carbophene. 3-carbophene is a member of a novel class of two-dimensional covalent organic framework, [N]-carbophenes (carbophenes). Using a high throughput method, we computed the formation energies and conduction properties of 3-, 4-, 5-, and 6-carbophenes with hydroxyl (OH), carbonyl (CO), nitro (NO $_2$ ), amine (NH $_2$ ), carboxyl (COOH) functional groups replacing hydrogen terminating agents. Five hundred and nine structures with randomly …
Unravelling 2,4-D -- biochar interactions by molecular dynamics: adsorption modes and surface functionalities
School of Chemistry, University of Edinburgh（爱丁堡大学化学学院）；UK Biochar Research Centre, School of GeoSciences, University of Edinburgh（爱丁堡大学地球科学学院英国生物炭研究中心）
Machine-learned exchange-correlation functionals for molecules, solids, and reactive surfaces
Harvard University（哈佛大学）；Massachusetts Institute of Technology（麻省理工学院）；Robert Bosch LLC Research and Technology Center（罗伯特博世有限责任公司研究与技术中心）；Initiative for Computational Catalysis, Flatiron Institute（计算催化倡议，平顿研究所）
